Contextual Injection of Quality Measures into Software Engineering Processes

Despite improvements in software engineering processes and tools, concrete preventative and analytical software quality assurance activities are still typically manually triggered and determined, resulting in missed or untimely quality opportunities and increased project overhead. Quality goals, when defined, lack holistic environmental support for automated performance measurement and governance that is tightly integrated in the low-level operational software engineering processes. This results in higher quality risks and cost risks. Based on adaptive process management, an approach is presented that injects situationally-determined quality measure proposals into the concrete workflows of software engineers, using contextual semantic knowledge and multi-agent quality goal tracking and decision-making. Our evaluation shows the feasibility of the approach for automatically providing timely quality measure guidance to software engineers without disrupting their current activities. This supports process governance while reducing quality risks and costs during software development